Data Engineer: Databricks & GCP AI Workflows | Flexible

Agileengine; Sucre; On-site; COP 264,690,000 - 397,035,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

You will design and optimize data pipelines using Databricks, PySpark, and SQL; build workflows; integrate with GCP, BigQuery, and Delta Lake; implement data quality and production controls; collaborate across teams.

Qualifications

• 5+ years of hands-on experience with Databricks and PySpark.
• Advanced SQL and data-processing skills.
• Hands-on experience with GCP, particularly BigQuery.
• Experience with Delta Lake and modern data lake/lakehouse architectures.
• Strong understanding of ETL/ELT, data pipeline design, performance optimization, and data quality.
• Experience building reliable, scalable, production-grade data solutions.
• Strong analytical and troubleshooting skills.
• Understanding of software engineering practices including testing, version control, deployment, monitoring, and production support.
• Upper-intermediate English level.

Responsibilities

• Design, develop, and optimize scalable ETL/ELT data pipelines using Databricks, PySpark, and SQL.
• Build and operationalize agentic workflows to automate data engineering and operational processes such as data validation, issue identification, troubleshooting, and workflow execution.
• Integrate agentic capabilities with existing Databricks, GCP, BigQuery, and Delta Lake environments.
• Develop data pipelines and processing solutions to support new business requirements and datasets.
• Build reusable frameworks and components that can be leveraged across multiple data engineering and business use cases.
• Implement data quality checks, monitoring, validation, exception handling, and production controls.
• Optimize PySpark and SQL workloads for performance, reliability, and scalability.
• Support testing, deployment, productionization, and ongoing enhancement of data and agentic solutions.
• Troubleshoot complex data and production issues and implement sustainable solutions.
• Collaborate with business, data engineering, and platform teams to identify further automation opportunities.

Skills

Databricks

PySpark

SQL

Data processing

ETL/ELT design

Troubleshooting

Production-grade data solutions

Analytics

Tools

GCP - BigQuery

Delta Lake

Job description

AgileEngine is seeking a Data Engineer with strong Databricks and GCP experience to develop scalable ETL/ELT pipelines and productionize agentic workflows for data engineering automation.

You will design and optimize data pipelines using Databricks, PySpark, and SQL; build workflows; integrate with GCP, BigQuery, and Delta Lake; implement data quality and production controls; collaborate across teams.